Abstractive Arabic Text Summarization Using Hyperparameter Tuned Denoising Deep Neural Network

作     者：Ibrahim M.Alwayle Hala J.Alshahrani Saud S.Alotaibi Khaled M.Alalayah Amira Sayed A.Aziz Khadija M.Alaidarous Ibrahim Abdulrab Ahmed Manar Ahmed Hamza 

作者机构：Department of Computer ScienceCollege of Science and ArtsSharurahNajran UniversitySharurahSaudi Arabia Department of Applied LinguisticsCollege of LanguagesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information SystemsCollege of Computing and Information SystemUmm Al-Qura UniversityMakkahSaudi Arabia Department of Digital MediaFaculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Computer DepartmentApplied CollegeNajran UniversityNajran66462Saudi Arabia Department of Computer and Self DevelopmentPreparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia 

出 版 物：《Intelligent Automation & Soft Computing》 (智能自动化与软计算（英文）)

年 卷 期：2023年第38卷第11期

页      面：153-168页

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2022R281) Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:22UQU4210118DSR33 The authors are thankful to the Deanship of ScientificResearch atNajranUniversity for funding thiswork under theResearch Groups Funding Program Grant Code(NU/RG/SERC/11/7) 

主　　题：Text summarization deep learning denoising deep neural networks hyperparameter tuning Arabic language 

摘      要：ive Arabic Text Summarization using Hyperparameter Tuned Denoising Deep Neural Network(AATS-HTDDNN)*** presented AATS-HTDDNN technique aims to generate summaries of Arabic *** the presented AATS-HTDDNN technique,the DDNN model is utilized to generate the *** study exploits the Chameleon Swarm Optimization(CSO)algorithm to fine-tune the hyperparameters relevant to the DDNN model since it considerably affects the summarization *** phase shows the novelty of the current *** validate the enhanced summarization performance of the proposed AATS-HTDDNN model,a comprehensive experimental analysis was *** comparison study outcomes confirmed the better performance of the AATS-HTDDNN model over other approaches.